Taking handheld photos in low-light conditions is challenging. Since less light is available, longer exposure times are needed to obtain an adequately exposed image. A consequence of longer exposure times is that the quality of the photo is more susceptible to camera movement which, in turn, results in a blurred image. In order to avoid camera movement, photographers frequently use a tripod to support a camera. However, use of a tripod to remove movement is not always practical. This is particularly relevant with the proliferation of mobile phones with built-in cameras. Consequently, in many, if not almost all circumstances, camera shake is likely to be an issue resulting to blurry pictures.
Blur may be removed, with varying degrees of success, from a blurred image in an attempt to recover a latent sharp image. Known techniques utilize a single blur kernel to deblur an entire image using deconvolution. These known techniques require user input to identify a region in the blurred image from which to estimate a blur kernel. Further, known techniques are very computationally intensive and high in memory usage.
It will thus be appreciated that it is challenging for casual users, without trained eyes, to select an appropriate region for blur kernel estimation. This, and long computation times, can become a frustrating process for users trying to deblur an image. Accordingly, providing assistance to a user in selecting a region for blur kernel estimation would be very beneficial.